Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter?

Pistel M, Laun FB, Bickelhaupt S, Dada A, Weiland E, Niederdränk T, Uder M, Janka RM, Wenkel E, Ohlmeyer S (2022)


Publication Type: Journal article

Publication year: 2022

Journal

DOI: 10.1002/jmri.28150

Abstract

Background: Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel-by-voxel basis or using volume-averaged signal. Purpose: Investigate and compare DKI parameters' diagnostic performance using voxel-by-voxel and volume-averaged signal fit approach. Study type: Retrospective. Study population: A total of 104 patients, aged 24.1–86.4 years. Field Strength/Sequence: A 3 T Spin-echo planar diffusion-weighted sequence with b-values: 50 s/mm2, 750 s/mm2, and 1500 s/mm2. Dynamic contrast enhanced (DCE) sequence. Assessment: Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel-by-voxel basis and with volume-averaged signal. Diagnostic performance of DKI parameters (Formula presented.) (kurtosis corrected diffusion coefficient) and kurtosis (Formula presented.) was compared between both approaches. Statistical Tests: Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t-test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient. Results: DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel-by-voxel and volume-averaged approach were 2.00 vs. 1.28 ((Formula presented.) in μm2/msec), 2.03 vs. 1.26 ((Formula presented.) in μm2/msec), 0.54 vs. 0.90 ((Formula presented.)), 0.55 vs. 0.99 ((Formula presented.)). AUC for voxel-by-voxel and volume-averaged fit were 0.9494 and 0.9508 ((Formula presented.)); 0.9175 and 0.9298 ((Formula presented.)). For both, AUC did not differ significantly (P = 0.20). Correlation of values between the two approaches was very high (r = 0.99 for (Formula presented.) and r = 0.97 for (Formula presented.)). Data Conclusion: Voxel-by-voxel and volume-averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI. Evidence Level: 3. Technical Efficacy: Stage 3.

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How to cite

APA:

Pistel, M., Laun, F.B., Bickelhaupt, S., Dada, A., Weiland, E., Niederdränk, T.,... Ohlmeyer, S. (2022). Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter? Journal of Magnetic Resonance Imaging. https://doi.org/10.1002/jmri.28150

MLA:

Pistel, Mona, et al. "Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter?" Journal of Magnetic Resonance Imaging (2022).

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